Currently, when a user listens to streaming media (such as a song from a radio station), because a piece of complete streaming media needs to be played for a period of time (for example, 3 to 4 minutes), how to continuously track streaming media in a playback process to display accurate streaming media information in real time is particularly important. In the existing technology, streaming media may be tracked by using an audio fingerprint technology. An audio fingerprint refers to a content-based compact digital signature that may represent important acoustic features of a piece of music. The audio fingerprint technology generally includes two parts: a fingerprint extraction algorithm for calculating important auditory features and a fingerprint comparison algorithm for performing effective searching in a fingerprint database. When an unknown audio needs to be identified, audio features of the unknown audio are calculated first according to the fingerprint extraction algorithm, and comparison is then performed according to the fingerprint comparison algorithm between the audio features and a large number of audio fingerprints stored in the fingerprint database, to identify a corresponding audio. An effective audio fingerprint technology can be used to correctly identify, in the database, an original version of a distorted unknown audio on which various signal processing may be performed.
An objective of an audio fingerprint system is to search for a corresponding audio by receiving an audio signal and using a pre-constructed audio fingerprint database, to identify a predetermined audio. According to application fields, the audio fingerprint system is used for broadcast monitors, CF identification, and file filtering. In order to effectively use the audio fingerprint system in the application fields, even in various distortion situations, a high identification rate and a high searching speed are also needed. Specifically, in order to filter a file in a P2P field or a UCC field, audio fingerprint data formed by hundreds of thousands of audio files each of which has its own copyright needs to be quickly and accurately searched for. For real-time processing in a broadcast monitoring field and a file filtering field in which operations are performed based on a high-capacity audio fingerprint database, the identification speed is one of the most important factors.
In the existing technology, tracking streaming media by using an audio fingerprint technology includes: first performing framing on an audio signal of an audio segment; then determining a key frame based on a start point detection algorithm, extracting an audio fingerprint of the key frame, correspondingly storing the audio fingerprint and streaming media information of the key frame into a hash table, inputting, by a user, the audio segment to search for the audio fingerprint, and obtaining the audio fingerprint based on the audio signal of the audio segment; and then matching corresponding streaming media information from the hash table according to the audio fingerprint, and obtaining streaming media information including the audio segment, to implement identification of streaming media. In a streaming media playback process, the audio fingerprint matching needs to be continuously performed until the streaming media playback is ended. According to the foregoing manner of tracking streaming media, after streaming media is identified, audio fingerprint matching, being a calculation wasting time and energy, is still continuously performed, which greatly consumes calculation resources and memory resources. Generally, a response time of searching is long (for example, one second). In addition, such a matching calculation is continuously performed, and if there is a slight difference between two matching results (because a situation of repeated streaming media of which a name and a name of a singer are slightly different exists), complexity of streaming media identification (such as result ranking) may further be increased.
Therefore, it is necessary to put forward a new technical solution, so as to solve the foregoing technical problem that in the foregoing manner of tracking streaming media, after streaming media is identified, audio fingerprint matching is still continuously performed, which wastes calculation resources and memory resources and increases complexity of streaming media identification.